The term federated learning was introduced by [1]}.
Federated learning (FL) is machine learning setting where a set of \(\mathbf {m}\)  clients (e.g., mobile devices) collaboratively train a model under the orchestration of a federated server (e.g., service provider), while the training data of clients is stored locally and not exchanged [2]}.
The federated server orchestrates the collaborative training process, by repeating the following steps until training is converged:
